Event Prediction in Event-Centric Knowledge Graphs Using LLM

Abstract

The dataset provided by the Knowledge Graph Reasoning Challenge for Social Issues (KGRC4SI) is an event-centric knowledge graph representation of avatar behavior in a virtual space. Therefore, it contains information on the entire virtual space, including parts of the virtual space that are hidden in the video. However, some information cannot be obtained by any means, for example, when sensor data from the real world is collected. In this paper, we report a method for predicting the hidden parts using LLM and the results of experiments using this method, using the KGRC4SI dataset as complete data for training.